Classification of satellite imagery of vessels is currently a manual process that requires a human analyst trained to recognize primary physical features unique to each ship type. Traditional classification methods identify vessels based on appearance group, hull type, and upright sequence. An analyst examines characteristic features such as the size, shape, and location of superstructure, the shape of the hull, the number and location of islands, and the location of upright devices and machinery as these characteristics appear in the vessel profile. The observed sequence of features is compared to a set of known vessel silhouettes to identify the vessel class.
The comparison method of classification described above requires analysts to memorize an entire library of vessel silhouettes in order for classification to be completed effectively and accurately. With this method, classification can only be completed manually, and only by highly skilled analysts. In addition, the process of classification is not automated; in certain situations, it may be desirable to classify vessels very quickly, for example in a harbor or congested port where many vessels are present. In a congested port or chokepoint, an analyst may be unable to accurately identify vessels of interest as quickly as the mission requires.
Furthermore, features and ship silhouettes used for traditional vessel classification present a side-profile view, which does not easily translate to features that are visible in a top plan view, such as those features extracted from overhead commercial imagery. Stated differently, characteristic appearance information such as hull shape and upright sequence, which is typically used to classify vessels, is not easily extracted from overhead commercial imagery. As a result, an analyst presented with satellite imagery of vessels will most likely not be able to employ traditional methods to accurately classify each ship. What is desired is a new method for classifying vessels using features extracted from overhead imagery, which will allow analysts to quickly and effectively classify vessels in situations where traditional methods are inapplicable.
In view of the above, one object of the present invention is to provide an automated image classification system and method that effectively classifies vessels using an input from satellite overhead imagery. Another object of the present invention is to provide an automated image classification system and method that can classify vessels with greater speed and throughput than prior art manual systems. Yet another object of the present invention is to provide an automated image classification system and method that can function to classify vessels without requiring a dedicated analyst. Still another object of the present invention is to provide an automated image classification system and method that uses a top plan view of the vessel deck instead of a side elevational view of a vessel hull and superstructure profile to classify a vessel. These and other advantages of the invention, as well as additional inventive features, will be apparent from the description of the invention provided herein.